A New Method for Identification and Analysis of Persistent Scatterers in Series of SAR Images

Synthetic aperture radar (SAR) interferometry is a powerful technology for measuring slow terrain movements. The extraction of this information is a complex task, because the phase of the signal is measured only modulo 2pi and is affected by noise and systematic terms. The persistent scatterer (PS) approach brought important advances in the solution of this problem. In this work, we present a new method, named persistent scatterer pairs (PSP) method, for the identification and the analysis of PS in series of full resolution SAR images. The problems coming from orbital and atmosphere phase artifacts are effectively overcome by exploiting their spatial correlation, without using model based interpolations or fits, which can be advantageous when the atmospheric artifacts or the displacement to be retrieved are not very well described by the models used in the standard PS approach. Moreover, the proposed method does not need a preprocessing to calibrate the data and is insensitive to the density of PS candidates, it is able to identify PS in natural terrains and PS characterized by non linear movements, is computationally efficient and highly parallelizable. The results obtained on real ERS SAR data confirm the validity of the proposed approach.